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Dynamic model development for submerged membrane filtration process using recurrent artificial neural network with control application

Modeling of membrane filtration process is challenging task because it is involves many interactions from biological and physical operation behavior. Membrane fouling in filtration process is too complex to understand and to derive a robust model is not possible. The aim of this paper is to study th...

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Main Authors: Yusuf, Zakariah, Abdul Wahab, Norhaliza, Sahlan, Shafishuhaza
Format: Conference or Workshop Item
Language:English
Published: 2015
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/61996/1/NorhalizaAbdWahab2015_DynamicModelDevelopmentforSubmergedMembrane.pdf
http://eprints.utm.my/id/eprint/61996/
http://www.utm.my/iicist/
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spelling my.utm.619962017-05-30T00:19:30Z http://eprints.utm.my/id/eprint/61996/ Dynamic model development for submerged membrane filtration process using recurrent artificial neural network with control application Yusuf, Zakariah Abdul Wahab, Norhaliza Sahlan, Shafishuhaza TK Electrical engineering. Electronics Nuclear engineering Modeling of membrane filtration process is challenging task because it is involves many interactions from biological and physical operation behavior. Membrane fouling in filtration process is too complex to understand and to derive a robust model is not possible. The aim of this paper is to study the potential of neural network based dynamic model for submerged membrane filtration process. The purpose of the model is to represent the dynamic behavior of the filtration process therefore suitable control strategy and tuning can be developed to control the filtration process more effectively. In this work, a recurrent neural network (RNN) structure was employed to perform the dynamic model of the filtration process. The random step was applied to the suction pump to obtained the permeate flux and Transmembrane Pressure (TMP) dynamic. The model was evaluated in term of %R2, root mean square error (RMSE,) and mean absolute deviation (MAD). Proportional integral derivative (PID) controller was implemented to the model for different control strategies and several tuning gains were tested for the effective filtration control. The result of proposed modeling technique showed that the RNN structure is able to model the dynamic behavior of the filtration process below critical flux condition. The developed model also can be a reliable assistance for the control strategy development in the filtration process. 2015 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/61996/1/NorhalizaAbdWahab2015_DynamicModelDevelopmentforSubmergedMembrane.pdf Yusuf, Zakariah and Abdul Wahab, Norhaliza and Sahlan, Shafishuhaza (2015) Dynamic model development for submerged membrane filtration process using recurrent artificial neural network with control application. In: The 1st ICRIL-International Conference on Innovation in Science and Technology (IICIST 2015), 20 April, 2015, Kuala Lumpur, Malaysia. http://www.utm.my/iicist/
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Yusuf, Zakariah
Abdul Wahab, Norhaliza
Sahlan, Shafishuhaza
Dynamic model development for submerged membrane filtration process using recurrent artificial neural network with control application
description Modeling of membrane filtration process is challenging task because it is involves many interactions from biological and physical operation behavior. Membrane fouling in filtration process is too complex to understand and to derive a robust model is not possible. The aim of this paper is to study the potential of neural network based dynamic model for submerged membrane filtration process. The purpose of the model is to represent the dynamic behavior of the filtration process therefore suitable control strategy and tuning can be developed to control the filtration process more effectively. In this work, a recurrent neural network (RNN) structure was employed to perform the dynamic model of the filtration process. The random step was applied to the suction pump to obtained the permeate flux and Transmembrane Pressure (TMP) dynamic. The model was evaluated in term of %R2, root mean square error (RMSE,) and mean absolute deviation (MAD). Proportional integral derivative (PID) controller was implemented to the model for different control strategies and several tuning gains were tested for the effective filtration control. The result of proposed modeling technique showed that the RNN structure is able to model the dynamic behavior of the filtration process below critical flux condition. The developed model also can be a reliable assistance for the control strategy development in the filtration process.
format Conference or Workshop Item
author Yusuf, Zakariah
Abdul Wahab, Norhaliza
Sahlan, Shafishuhaza
author_facet Yusuf, Zakariah
Abdul Wahab, Norhaliza
Sahlan, Shafishuhaza
author_sort Yusuf, Zakariah
title Dynamic model development for submerged membrane filtration process using recurrent artificial neural network with control application
title_short Dynamic model development for submerged membrane filtration process using recurrent artificial neural network with control application
title_full Dynamic model development for submerged membrane filtration process using recurrent artificial neural network with control application
title_fullStr Dynamic model development for submerged membrane filtration process using recurrent artificial neural network with control application
title_full_unstemmed Dynamic model development for submerged membrane filtration process using recurrent artificial neural network with control application
title_sort dynamic model development for submerged membrane filtration process using recurrent artificial neural network with control application
publishDate 2015
url http://eprints.utm.my/id/eprint/61996/1/NorhalizaAbdWahab2015_DynamicModelDevelopmentforSubmergedMembrane.pdf
http://eprints.utm.my/id/eprint/61996/
http://www.utm.my/iicist/
_version_ 1643655298706046976
score 13.244745

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